Systematic biases in reference-based plasma cell-free DNA fragmentomic profiling.

Plasma cell-free DNA (cfDNA) fragmentation patterns are emerging directions in cancer liquid biopsy with high translational significance. Conventionally, the cfDNA sequencing reads are aligned to a reference genome to extract their fragmentomic features. In this study, through cfDNA fragmentomics profiling using different reference genomes on the same datasets in parallel, we report systematic biases in such conventional reference-based approaches. The biases in cfDNA fragmentomic features vary among races in a sample-dependent manner and therefore might adversely affect the performances of cancer diagnosis assays across multiple clinical centers. In addition, to circumvent the analytical biases, we develop Freefly, a reference-free approach for cfDNA fragmentomics profiling. Freefly runs ∼60-fold faster than the conventional reference-based approach while generating highly consistent results. Moreover, cfDNA fragmentomic features reported by Freefly can be directly used for cancer diagnosis. Hence, Freefly possesses translational merit toward the rapid and unbiased measurement of cfDNA fragmentomics.

Generalizable transcriptome-based tumor malignant level evaluation and molecular subtyping towards precision oncology.

In cancer treatment, therapeutic strategies that integrate tumor-specific characteristics (i.e., precision oncology) are widely implemented to provide clinical benefits for cancer patients. Here, through in-depth integration of tumor transcriptome and patients' prognoses across cancers, we investigated dysregulated and prognosis-associated genes and catalogued such important genes in a cancer type-dependent manner. Utilizing the expression matrices of these genes, we built models to quantitatively evaluate the malignant levels of tumors across cancers, which could add value to the clinical staging system for improved prediction of patients' survival. Furthermore, we performed a transcriptome-based molecular subtyping on hepatocellular carcinoma, which revealed three subtypes with significantly diversified clinical outcomes, mutation landscapes, immune microenvironment, and dysregulated pathways. As tumor transcriptome was commonly profiled in clinical practice with low experimental complexity and cost, this work proposed easy-to-perform approaches for practical clinical promotion towards better healthcare and precision oncology of cancer patients.

DNA methylation analysis explores the molecular basis of plasma cell-free DNA fragmentation.

Plasma cell-free DNA (cfDNA) are small molecules generated through a non-random fragmentation procedure. Despite commendable translational values in cancer liquid biopsy, however, the biology of cfDNA, especially the principles of cfDNA fragmentation, remains largely elusive. Through orientation-aware analyses of cfDNA fragmentation patterns against the nucleosome structure and integration with multidimensional functional genomics data, here we report a DNA methylation - nuclease preference - cutting end - size distribution axis, demonstrating the role of DNA methylation as a functional molecular regulator of cfDNA fragmentation. Hence, low-level DNA methylation could increase nucleosome accessibility and alter the cutting activities of nucleases during DNA fragmentation, which further leads to variation in cutting sites and size distribution of cfDNA. We further develop a cfDNA ending preference-based metric for cancer diagnosis, whose performance has been validated by multiple pan-cancer datasets. Our work sheds light on the molecular basis of cfDNA fragmentation towards broader applications in cancer liquid biopsy.

Msuite2: All-in-one DNA methylation data analysis toolkit with enhanced usability and performance.

DNA methylation is an important epigenetic regulator that plays crucial roles in various biological processes. Recent developments in experimental approaches and dramatic expansion of sequencing capacities have imposed new challenges in the analysis of large-scale, cross-species DNA methylation data. Hence, user-friendly toolkits with high usability and performance are in urgent need. In this work, we present Msuite2, an easy-to-use, all-in-one, and universal toolkit for DNA methylation data analysis and visualization with high flexibility, usability, and performance. Msuite2 is among the fastest tools in read alignment (in particular, it runs as much as 5x faster than its predecessor, Msuite1) with low computing resource usage. In addition, Msuite2 shows both balanced and high performance in terms of mapping efficiency and accuracy, demonstrating high potential to facilitate the investigation and application of large-scale DNA methylation analysis in various biomedical studies. Msuite2 is freely available at https://github.com/hellosunking/Msuite2/.

New Chromatin Run-On Reaction Enables Global Mapping of Active RNA Polymerase Locations in an Enrichment-free Manner.

The development of a simple and cost-effective method to map the distribution of RNA polymerase II (RNPII) genome-wide at a high resolution is highly beneficial to study cellular transcriptional activity. Here we report a mutation-based and enrichment-free global chromatin run-on sequencing (mGRO-seq) technique to locate active RNPII sites genome-wide at near-base resolution. An adenosine triphosphate (ATP) analog named N6-allyladenosine triphosphate (a6ATP) was designed and could be incorporated into nascent RNAs at RNPII-located positions during a chromatin run-on reaction. By treatment of the run-on RNAs with a mild iodination reaction and subjection of the products to reverse transcription into complementary DNA (cDNA), base mismatch occurs at the original a6A incorporation sites, thus making the RNPII locations detected in the high-throughput cDNA sequencing. The mGRO-seq yields both the map of RNPII sites and the chromatin RNA abundance and holds great promise for the study of single-cell transcriptional activity.

Recent Advances in Liquid Biopsy of Brain Cancers.

Brain cancers are among the top causes of death worldwide. Although, the survival rates vary widely depending on the type of the tumor, early diagnosis could generally benefit in better prognosis outcomes of the brain cancer patients. Conventionally, neuroimaging and biopsy are the most widely used approaches in diagnosis, subtyping, and prognosis monitoring of brain cancers, while emerging liquid biopsy assays using peripheral blood or cerebrospinal fluid have demonstrated many favorable characteristics in this task, especially due to their minimally invasive and easiness in sampling nature. Here, we review the recent studies in the liquid biopsy of brain cancers. We discuss the methodologies and performances of various assays on diagnosis, tumor subtyping, relapse prediction as well as prognosis monitoring in brain cancers, which approaches have made a big step toward clinical benefits of brain cancer patients.